Computational Intelligence based construction of a Body Condition Assessment system for cattle

2013 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA) Pub Date : 2013-07-15 DOI:10.1109/CIVEMSA.2013.6617418

Rafael Tedin, J. Becerra, R. Duro, F. López-Peña

{"title":"Computational Intelligence based construction of a Body Condition Assessment system for cattle","authors":"Rafael Tedin, J. Becerra, R. Duro, F. López-Peña","doi":"10.1109/CIVEMSA.2013.6617418","DOIUrl":null,"url":null,"abstract":"The objective of this paper is to describe a Computational Intelligence based Automatic Body Conditioning System for cattle we have called Automatic Body Condition Assessment (ABiCA). It is an automatic body condition scoring system for dairy cattle that aims to overcome the flaws of the subjective and time consuming scoring task that is usually carried out by experts. No special set-ups are needed since the system uses pictures taken using normal hand-held cameras. ABiCA is split into two components. A first component for the segmentation of the rear-end shape of a cow from its picture through Active Shape Models Active Shape Models (ASMs) that are evolved using an evolutionary algorithm. The second component is in charge of estimating the Body Condition Score (BCS) of a cow from the shape provided by the ASM. Several classifiers and a symbolic regression function evolved by means of genetic programming techniques are tested for this task. The whole system is tested over a set of images coming from different cattle farms and its goodness provided in terms of the classifications obtained by a set of experts.","PeriodicalId":159100,"journal":{"name":"2013 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIVEMSA.2013.6617418","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 2

Abstract

The objective of this paper is to describe a Computational Intelligence based Automatic Body Conditioning System for cattle we have called Automatic Body Condition Assessment (ABiCA). It is an automatic body condition scoring system for dairy cattle that aims to overcome the flaws of the subjective and time consuming scoring task that is usually carried out by experts. No special set-ups are needed since the system uses pictures taken using normal hand-held cameras. ABiCA is split into two components. A first component for the segmentation of the rear-end shape of a cow from its picture through Active Shape Models Active Shape Models (ASMs) that are evolved using an evolutionary algorithm. The second component is in charge of estimating the Body Condition Score (BCS) of a cow from the shape provided by the ASM. Several classifiers and a symbolic regression function evolved by means of genetic programming techniques are tested for this task. The whole system is tested over a set of images coming from different cattle farms and its goodness provided in terms of the classifications obtained by a set of experts.

查看原文

微信好友朋友圈 QQ好友复制链接

本刊更多论文

基于计算智能的牛体况评估系统构建

本文的目的是描述一个基于计算智能的牛自动身体调节系统，我们称之为自动身体状态评估(ABiCA)。它是一种奶牛身体状况自动评分系统，旨在克服通常由专家进行主观且耗时的评分任务的缺陷。由于该系统使用的是普通手持相机拍摄的照片，因此无需特殊设置。ABiCA分为两个部分。第一部分是利用主动形状模型从图像中分割出奶牛的后端形状，主动形状模型是利用一种进化算法进化而来的。第二个组件负责根据ASM提供的形状估算奶牛的身体状况评分(BCS)。几个分类器和一个符号回归函数进化的手段遗传规划技术进行了测试。整个系统通过来自不同牛场的一组图像进行测试，并根据一组专家获得的分类提供其优点。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文去求助

来源期刊

2013 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA)

自引率

0.00%

发文量

期刊最新文献

Intelligent SVM based food intake measurement system An ANN based system for forecasting ship roll motion Computational Intelligence based construction of a Body Condition Assessment system for cattle Facial expression cloning with fuzzy set clustering The impact of motion in virtual environments on memorization performance